You don't have to know a lot about probability theory to use a Bayesian probability model for financial forecasting. The Bayesian method can help you refine probability estimates using an ...

The point-in-time rating transition probability, for PD term structure for IFRS9 expected credit loss estimation and CCAR stress testing, is estimated by A forward ordinal probability model structured ...

In our August 2014 analysis, we used the example of one day's data to prove this simple formula is a very poor description of the relationship between credit spreads and default probabilities.

Paul Kabaila, Hannes Leeb, On the Large-Sample Minimal Coverage Probability of Confidence Intervals after Model Selection, Journal of the American Statistical Association, Vol. 101, No. 474 (Jun., ...

For example, things like interest rates, inflation, and stock prices often influence each other. Standard decision tree models do not inherently account for these interdependencies, potentially ...

For instance, studies have delineated how bidimensional risk models with dependent claim sizes using Sarmanov-type structures can derive both finite-time and infinite-time ruin probabilities ...

Our model estimates therefore suggest that the Basel II requirement of assigning at least a 0.03% default transition probability is conservative. For example, for the A-rated category the top of the ...

"Waiting to be sold: researchers develop model to predict probability of home sales." ScienceDaily. ScienceDaily, 18 March 2017. <www.sciencedaily.com / releases / 2017 / 03 / 170314135449.htm>.

ABSTRACT The aim of validating default probabilities is to analyze whether these are not too low. For small sample sizes, however, there are not enough observations available to detect excessively low ...